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Efficiency Enhancement in Turbomachinery: Bridging Numerical Modeling and Experimental Validation for Fluid Dynamics Advancements

Abstract

Turbomachinery plays a pivotal role in various industries, from aviation and power generation to automotive and maritime applications. Enhancing the efficiency of turbomachinery is of paramount importance for energy conservation and performance optimization in these sectors. This research abstract provides an overview of the ongoing efforts to bridge numerical modeling and experimental validation in the field of fluid dynamics to advance turbomachinery efficiency. The first section introduces turbomachinery and underscores its significance across industries, emphasizing the need for efficiency improvements. The second section delves into numerical modeling techniques, particularly Computational Fluid Dynamics (CFD), elucidating their utility in analyzing turbomachinery while also addressing their inherent advantages and limitations. Subsequently, experimental validation methods, including wind tunnel testing, water tunnel testing, and real-world measurements, are presented as crucial tools in validating numerical models and gaining insights from the real-world environment. The fourth section explores the challenges encountered when reconciling numerical results with experimental data, focusing on accuracy, boundary conditions, and model simplifications. In response to these challenges, the fifth section highlights methodologies for effectively integrating numerical and experimental data to enhance turbomachinery analysis, emphasizing the synergistic benefits of this combined approach in terms of accuracy and efficiency. Advancements in fluid dynamics research applicable to turbomachinery design are discussed in the sixth section, showcasing innovative concepts that hold the potential for efficiency improvements. The seventh section provides case studies and practical applications, illustrating instances where the proposed methodology has successfully led to efficiency enhancements in specific turbomachinery applications. The eighth section identifies future research opportunities, suggesting potential areas for further exploration in the realm of turbomachinery efficiency enhancement. Emerging technologies and approaches that can be leveraged to advance fluid dynamics in turbomachinery are also addressed.

Keywords

Turbomachinery efficiency, Numerical modeling, Computational Fluid Dynamics (CFD), Fluid dynamics studies, Experimental validation, Machine learning (ML), Emerging technologies

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